The quantity and composition of household food waste: Implications for policy

Studies on food waste in Southeast Asia are currently limited, with a notable absence of comparative analyses investigating the volume and composition of food waste in urban and rural areas through direct measurement. This study aimed to analyze the differences in the quantity, composition, and drivers of household food waste between urban and rural areas. Household food waste was assessed through waste compositional analysis for food and diaries for beverages. This cross-sectional study included 215 households in Bogor Regency, Indonesia. Comparisons between the two areas were performed using an independent t-test. The average of household food waste in Bogor Regency was 77 kg/cap/year (edible 37.7%, inedible 62.3%). Household food waste was higher in urban areas (79.4 kg/cap/year) than in rural areas (45.8 kg/cap/year) (p<0.001). Cereals, tubers and their derivatives (especially rice) and vegetables were the major contributors to edible food waste, whereas fruits were the main contributors to inedible food waste in both areas. Food waste drivers were spoilage/staleness/moldiness, changes in texture, short shelf life, cooking too much, and plate leftovers. Households in urban areas had a higher quantity of food waste and disposed of more edible food than those in rural areas. Meanwhile, the drivers of food waste generation were similar in both areas. Understanding the quantity, composition, and drivers of household food waste is pivotal for developing effective awareness campaigns and fostering behavioral changes to prevent household food waste.

The authors thank the Neys-van Hoogstraten Foundation and IPB University [Rian Diana, grant numbers: 01 /NHF-IPB I 2022] for funding this study.The funders did not involve in the study design, data collection, data analysis and preparation of the manuscript or decision to publish.
Please select the country of your main research funder (please select carefully as in some cases this is used in fee calculation).The authors declare no conflict of interest for this publication.

Introduction
Food loss and waste refer to a reduction in both the quantity and quality of food intended for human consumption along the food supply chain (1).Food waste (FW) occurs in retail (e.g., supermarkets and traditional markets), food services (e.g., restaurants, catering, canteens, and home consumption), households, and individuals (2-6).
The United Nations Environment Programme (UNEP) estimated that 17% of the food produced globally was discarded or not consumed.In 2019, the global average FW reached 121 kg/capita/year, equivalent to 931 million tons of food discarded at retail and consumer levels.Furthermore, households accounted for 61% of the total FW, while food services and retail contributed 26% and 13%, respectively (7).
Indonesia is the fourth-most populous country in the world.A food loss and waste study in Indonesia showed that in the last 20 years (2000-2019) the FW trend has increased from 39% to 55%, equivalent to 5-19 million tons per year.As much as 80% of FW came from households, 44% of which was edible food (8).However, there is a lack of detailed data on the characteristics of FW in Indonesia using direct measurement.Halving global FW per capita at the retail and consumer levels is one of the targets of the SDGs 12.To achieve this target, it is necessary to obtain accurate FW measurements to identify the contributing factors.
A systematic review revealed that no study in Southeast Asia has compared the quantity and composition of FW in urban and rural areas using direct measurements (20).To address this gap, the current study aimed to analyse the differences in household FW between urban and rural areas.

Methods
Household food waste measurements were conducted from 4-30 October 2022 using two methods: the waste compositional analysis (WCA) for solid waste (food) and diaries for beverages.
The WCA method was performed for eight consecutive days in accordance with the Indonesian National Standard (SNI) 19-3964-1994 for the collection and measurement of samples of urban waste generation and composition.Food waste from home trash bins was collected daily, sorted, and weighed per food type using a QME brand digital scale (QM-5140), with a precision of up to 2 g.This method is suitable for mixed solid waste, such as households (21,22), and its accuracy is high because of direct weighing and waste sorting by type and composition, eliminating the possibility of under-reporting (21).
The diary method was used to quantify drink waste, which was carried out over a seven-day period.Household members were requested to record the type and quantity of discarded beverages as well as the reason for discarding them.However, this method has several limitations, such as participant forgetting to record, unrecorded beverages, inaccurate estimation of discarded drink quantities, and changes in behavior during the recording period (23,24).To mitigate these limitations, clear instructions and a well-designed recording system were provided (24).Drink waste is typically disposed through a sink, making it impossible to use the WCA method.In this study, participants were instructed to record discarded beverages daily, and were provided with a measuring cup (100 ml) to measure the quantity of drinking waste.
The sample size was determined in accordance with SNI 19-3964-1994, which considered the population size, number of households, and average number of household members in the two selected sub-districts.A total of 215 households were selected for the FW measurements: 150 in urban areas and 65 in rural areas.Multistage random sampling was employed to select the households.This study was conducted in two areas of Bogor Regency, Indonesia, between October and September 2022.The Cibinong Sub-district was selected as the urban area, as it is the largest population center in the regency, and 100% of its area has urban characteristics.The Sukajaya subdistrict was chosen as a rural area because 63.6% of its area has rural characteristics.
The materials and tools used to measure FW using the WCA method were plastic bags, digital scales 0-400 kg, gloves, and recording forms.Diary form-filling guidelines, pens/pencils, and measuring cups were used to measure the diary method.
FW was calculated by weighting the number of households in each neighborhood and the number of family members in each household.An Independent sample t-test was conducted using IBM SPSS 21 to evaluate the differences in the quantity of FW between rural and urban areas.
To calculate the average FW in Bogor Regency in kg per capita per year, FW data were extrapolated, and the average FW generation data for urban and rural households were utilized.This method was adapted from the National Zero Waste Council, Canada (25).The total population (per village) of Bogor Regency at the end of 2022 was obtained from the Bogor Regency Population and Civil Registry Office.Additionally, extrapolation accounted for the total rural (390,047 people) and urban (5,037,021 people) populations in Bogor Regency (5,427,068 people).

This study was approved by the Human Research Ethics Committee of Bogor Agricultural
University (number 747/IT3.KEPMSM-IPB/SK/2022). Participants were fully informed of the study's objectives and benefits, and were provided with the right to withdraw at any time without consequences.Written informed consent was obtained from all participants prior to the interview.

Household Characteristics
The mean ages and educational levels of husbands and wives in urban areas were slightly higher than those in rural areas.Household income and expenditures in urban areas were almost double those in rural areas.(Table 1).

Quantity and composition of FW
This study revealed that the average FW in urban areas (79.4/cap/year) was almost double that in rural areas (45.8 kg/cap/year).Additionally, the proportion of edible FW was higher in urban areas (38.2%) than in rural areas (23.4%).The findings indicated that urban areas generated more FW per capita than rural areas for edible, inedible, and total FW (p<0.001) (Table 2).
Urban areas generated a greater quantity of FW, both in terms of type and composition, than rural areas.An exception to this trend was observed in inedible FW from fruits and their derivative products as well as inedible FW from cereals, tubers, and their derivative products.Urban households produced a higher proportion of edible FW than their rural counterparts.In urban areas, the most commonly discarded foods were cereals, tubers, and their derivatives (17.9 kg/cap/year), whereas rural areas had a higher disposal of vegetables (4.6 kg/cap/year).Fruit and its derivative products were the most commonly discarded inedible FW in both urban and rural areas, at a rate of 29.9 kg/cap/year and 21.7 kg/cap/year, respectively.Additionally, over 70% of the edible FW in both regions consists primarily of cereals, tubers, their derivatives, and vegetables.Conversely, over 70% of inedible FW consisted of fruits, their derivatives, and vegetables (Table 2).The most discarded edible waste per capita annually was rice (14.2 kg), carrots (0.9 kg), Chinese cabbage (0.7 kg), cabbage (0.6 kg), tempeh (0.6 kg), tofu (0.4 kg), guava (0.2 kg), and water apples (0.2 kg).Among the beverages, coffee (0.3 kg) and tea (0.2 kg) had the highest annual per capita waste, with animal food per capita being less than 0.1 kg (supplementary file).

Reasons for throwing away food
Five primary reasons were identified for discarding food: spoilage/staleness/moldiness, changes in texture, short shelf life, cooking too much, and plate leftovers.Sensory characteristics, such as staleness or moldiness and changes in texture, were the main reasons for throwing away rice and vegetables.The fruits were discarded because of moldiness, bruises, and changes in texture.Both animal-and plant-based foods have been discarded for various reasons.Dairy products were often discarded because they had been forgotten in the refrigerator and remained unconsumed.Frequent reasons for discarding meat, fish, and eggs were mold or mildew, and textural changes.Meanwhile, tofu and tempeh were discarded due to cooking too much, changes in texture, and unconsumed.
Bread was discarded when it was moldy or exceeded its best-before date.Inappropriate storage temperature and sensory changes (staleness or moldiness, and texture changes) were the main reasons for discarding packaged food (see Table 4).The reasons reported by the respondents in both urban and rural areas were almost identical for all types of food.

Discussion
The average FW found in this study (77 kg/cap/year) was comparable to the average FW in uppermiddle-income (76 kg/cap/year) and high-income (79 kg/cap/year) countries (7).In contrast, edible FW in upper-middle-income and high-income countries is higher, ranging from 50-65% (10-13,26) compared with the 37.7% found in this study, which is a lower-middle-income country.
The discarded food groups across countries displayed a similar composition, with staple foods, fruits, and vegetables being the main contributors to the total FW.This study aligns with previous research conducted in high-income countries, where staple diets consisting of rice (19) or bread (11,(27)(28)(29).
This study revealed that the average FW in urban areas was twice as high as that in rural areas, which is consistent with previous research conducted in lower, middle, and high-income countries (30,31).The quantity of FW in urban areas (79.4 kg/cap/year; 38.2% edible) exceeded that in rural areas (45.8 kg/cap/year; 23.4% edible); nevertheless, the composition and reasons for discarding food were similar between the two regions.The most commonly discarded edible FW in both processed food, contributing more significantly to FW than rural areas (34).Furthermore, many rural households convert their food waste into compost or use it as feed for pets or livestock (35,36), thereby reducing the amount of FW disposed in bins (35).
Modern retail, restaurants, and fast-food outlets are more abundant in urban areas than in rural areas.The growth of modern retail can affect traditional retail, consumer preferences, purchasing behavior, and food accessibility (32).Urban residents tend to prefer quick and convenient food preparation, leading to food over-purchasing, high consumption of processed foods, and foods from outside the home (restaurants, fast food outlets, and street food) (34).This trend contributes to the generation of food waste (34,37).

Policy Implication
Policies aimed at preventing household food waste should cover both preventive measures and food waste management.Prevention involves actions taken before edible food is discarded, whereas management focuses on dealing with food that is no longer suitable for consumption or has already been discarded.Prevention strategies can be implemented through awareness campaigns and initiatives to encourage behavioral changes.On the other hand, managing food waste can involve practices such as reuse and recycling by converting it into feed, compost, and eco-enzymes.
Prevention and reduction strategies should focus on urban areas and food groups that contribute significantly to edible FW (such as cereals, tubers, and their derivatives, particularly rice, vegetables, and legumes).Prioritizing the reuse and recycling of inedible food waste, particularly from fruits and vegetables, is essential to prevent its disposal in landfills.
Behavioral changes that focus on prolonging the shelf life of food and practicing proper storage can be implemented for all types of foods.Adjusting cooking portions and eating habits can be particularly beneficial for rice, vegetables, plant-based proteins such as tofu and tempeh, and cooked foods.Understanding food packaging data can help minimize food waste, particularly for bread and packaged goods.Finally, reusing food waste for feed and composting inedible fruits and vegetables at home rather than sending them to landfills is an important step in reducing food waste.

Research limitation
This study was conducted using direct FW measurements (Waste Composition Analysis) over eight consecutive days, ensuring high accuracy through sorting and weighing, based on type and composition.However, this study only captured a single point in time and did not include seasonal data.Additionally, the study only measured FW disposed of in household bins and did not consider FW disposed of or given to pets, plants, or other disposal channels.Despite these limitations, this study found that over 82.8% of household food waste was disposed of in the bin, with only 16.7% discarding FW onto plants for composting.

Conclusion
The quantity of household FW differs significantly between the urban and rural areas.However, based on the similar FW compositions and underlying reasons, strategies for FW prevention and reduction can be applied uniformly across both regions.Disparities exist in FW drivers, primarily depending on the type of food rather than the location of the resident with the following details: Initials of the authors who received each award • Grant numbers awarded to each author • The full name of each funder • URL of each funder website • Did the sponsors or funders play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript?• Did you receive funding for this work?Please add funding details. as follow-up to "Financial Disclosure Enter a financial disclosure statement that describes the sources of funding for the work included in this submission.Review the submission guidelines for detailed requirements.View published research articles from PLOS ONE for specific examples.This statement is required for submission and will appear in the published article if the submission is accepted.Please make sure it is accurate.Funded studies Enter a statement with the following details: Initials of the authors who received each award • Grant numbers awarded to each author • The full name of each funder • URL of each funder website • Did the sponsors or funders play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript?• Did you receive funding for this work?" as follow-up to "Financial Disclosure Enter a financial disclosure statement that describes the sources of funding for the work included in this submission.Review the submission guidelines for detailed requirements.View published research articles from PLOS ONE for specific examples.This statement is required for submission and will appear in the published article if the submission is accepted.Please make sure it is accurate.Funded studies Enter a statement with the following details: Initials of the authors who received each award • Grant numbers awarded to each author • The full name of each funder • URL of each funder website • Did the sponsors or funders play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript?• Did you receive funding for this work?"Competing Interests Use the instructions below to enter a competing interest statement for this submission.On behalf of all authors, disclose any competing interests that could be perceived to bias this work-acknowledging all financial support and any other relevant financial or nonfinancial competing interests.This statement is required for submission and will appear in the published article if the submission is accepted.Please make sure it is accurate and that any funding sources listed in your Funding Information later in the submission form are also declared in your Financial Disclosure statement.

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Table 2
Mean and standard deviation of FW quantity by type and food group in urban and rural areas (kg/cap/year)

Table 3
reveals that the average household FW in Bogor District is 77 kg/cap/year, consisting of 37.7% edible FW (29 kg/cap/year) and 62.3% inedible FW (48 kg/cap/year).Edible FW was mainly composed of cereals, tubers, and their derivatives at 16.9 kg/cap/year (mainly rice), and vegetables at 9.6 kg/cap/year.Meanwhile, inedible FW was dominated by fruits and their derivative products, accounting for 21.7 kg/cap/year (mainly bananas and mangoes).

Table 3
Mean and proportion of FW quantity by type and food group in Bogor District (kg/cap/year)

Table 4
Number of respondents by FW drivers